基于模糊神经网络(FNN)的赤潮预警预测研究

Research on the Prediction of Red Tide Based on the Fuzzy Neural Network

为研究各种理化因子与赤潮藻类浓度间的非线性对应规律和有效预测赤潮藻类浓度,构建了基于BP算法的一个四层模糊神经网络模型。将模糊神经网络(FNN)技术引入赤潮预测研究,并与普通BP网络、RBF网络的结果作比较,结果表明,该模型能够较好地反演出各种理化因子与夜光藻密度的非线性对应变化规律,有更好的预测功能。

In this paper, one four-layer fuzzy neural network using the Back Propagation Algorithm and fuzzy logic was built to study the nonlinear relationships between different physical-chemical factors and the denseness of red tide algae, and to anticipate the denseness of red tide algae. For the first time, the fuzzy neural network technology was applied to research the prediction of red tide. Compared with BP network and RBF network, the outcome of this method is better.